IVGCVSW-7606 IVGCVSW-7607 Add Resize and Reduce to Opaque Delegate
* Added 2 opaque delegate operators and associated test cases
* Removed IsDynamicTensor check from BatchMatMul as covered by IsValid.
Signed-off-by: John Mcloughlin <john.mcloughlin@arm.com>
Change-Id: If7c58cb23ae5c5b8a9451dddfd7b6dfcbf248d4c
diff --git a/delegate/opaque/src/Resize.hpp b/delegate/opaque/src/Resize.hpp
index e169697..509ae62 100644
--- a/delegate/opaque/src/Resize.hpp
+++ b/delegate/opaque/src/Resize.hpp
@@ -2,3 +2,221 @@
// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
+
+#pragma once
+
+#include <OpaqueDelegateUtils.hpp>
+
+namespace armnnOpaqueDelegate
+{
+
+TfLiteStatus ValidateResizeOperator(DelegateData& delegateData,
+ TfLiteOpaqueContext* tfLiteContext,
+ const armnn::TensorInfo& inputInfo,
+ const armnn::TensorInfo& outputInfo,
+ const armnn::ResizeDescriptor& descriptor)
+{
+ bool isSupported = false;
+ FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("RESIZE",
+ tfLiteContext,
+ IsResizeSupported,
+ delegateData.m_Backends,
+ isSupported,
+ armnn::BackendId(),
+ inputInfo,
+ outputInfo,
+ descriptor);
+
+ return isSupported ? kTfLiteOk : kTfLiteError;
+}
+
+TfLiteStatus VisitResizeOperator(DelegateData& delegateData,
+ TfLiteOpaqueContext* tfLiteContext,
+ TfLiteOpaqueNode* tfLiteNode,
+ int nodeIndex,
+ int32_t resizeOperatorCode)
+{
+ TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
+ TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+ // Gather input indices and use to get input tensor.
+ auto numInputs = TfLiteOpaqueNodeNumberOfInputs(tfLiteNode);
+ const int* inputTensors;
+ if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk)
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ",
+ nodeIndex);
+ return kTfLiteError;
+ }
+
+ // The first input contains the data of the image that should be resized [batch, height, width, channels]
+ const TfLiteOpaqueTensor* tfLiteInputTensor =
+ TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]);
+ if (IsDynamicTensor(tfLiteInputTensor))
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+ resizeOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ // The second input contains a size tensor. The size tensor contains two integer values
+ // that describe the new height and width of the image [new_height, new_width]
+ const TfLiteOpaqueTensor* tfLiteSizeTensor =
+ TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[1]);
+ if (IsDynamicTensor(tfLiteSizeTensor))
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+ resizeOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ // Gather output indices and use to get output tensors.
+ int numOutputs = 0;
+ const int* outputTensors;
+ if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk)
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ",
+ nodeIndex);
+ return kTfLiteError;
+ }
+
+ // The output tensor should have the shape [batch, new_height, new_width, channels]
+ const TfLiteOpaqueTensor* tfLiteOutputTensor =
+ TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
+ if (IsDynamicTensor(tfLiteOutputTensor))
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ",
+ resizeOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ const armnn::TensorInfo& inputTensorInfo =
+ GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor);
+ const armnn::TensorInfo& outputTensorInfo =
+ GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true);
+
+ std::string layerName("Resize");
+
+ // Fill descriptor
+ armnn::ResizeDescriptor desc;
+ switch (resizeOperatorCode)
+ {
+ case kTfLiteBuiltinResizeBilinear:
+ {
+ desc.m_Method = armnn::ResizeMethod::Bilinear;
+
+ layerName += "Bilinear:" + std::to_string(nodeIndex);
+
+ TfLiteResizeBilinearParams* bilinearOptions =
+ reinterpret_cast<TfLiteResizeBilinearParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
+
+ desc.m_AlignCorners = bilinearOptions->align_corners;
+ desc.m_HalfPixelCenters = bilinearOptions->half_pixel_centers;
+ break;
+ }
+ case kTfLiteBuiltinResizeNearestNeighbor:
+ {
+ desc.m_Method = armnn::ResizeMethod::NearestNeighbor;
+ layerName += "NearestNeighbor:" + std::to_string(nodeIndex);
+
+ TfLiteResizeNearestNeighborParams* nearestNeighborOptions =
+ reinterpret_cast<TfLiteResizeNearestNeighborParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
+
+ desc.m_AlignCorners = nearestNeighborOptions->align_corners;
+ desc.m_HalfPixelCenters = nearestNeighborOptions->half_pixel_centers;
+ break;
+ }
+ default:
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Unknown TfLite built in operation for Resize. "
+ "Given operator: #%d node #%d: ",
+ resizeOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+ }
+
+ // In Arm NN the values of the size input tensor [new_height, new_width] is saved in the operator
+ // descriptor. We have to read it from the input tensor and write it to the descriptor.
+
+ auto* sizeTensorDataPtr = static_cast<int*>(TfLiteOpaqueTensorData(tfLiteSizeTensor));
+ auto sizeTensorNumDimensions = TfLiteOpaqueTensorNumDims(tfLiteSizeTensor);
+ // The size tensor is only a 1D tensor -> [new_height, new width]
+ if (sizeTensorNumDimensions != 1)
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: The Size-Input-Tensor of the Resize operation is not allowed to be a "
+ "dynamic tensor. Operator: #%d node #%d: ",
+ resizeOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ // Get number of values in the size tensor
+ auto sizeTensorNumValues = TfLiteOpaqueTensorDim(tfLiteSizeTensor,0);
+ if (sizeTensorNumValues == 0)
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: The Size-Input-Tensor of the Resize operation is not allowed to be a "
+ "dynamic tensor. Operator: #%d node #%d: ",
+ resizeOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+ else if (sizeTensorNumValues != 2)
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: The Size-Input-Tensor of the Resize operation requires to "
+ "have a dimension of 2 [new_height, new width] but a tensor with a dimension of #%d was given. "
+ "Operator: #%d node #%d: ",
+ sizeTensorNumValues, resizeOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+ // get size tensor data
+ std::vector<int32_t> sizeTensorData(sizeTensorDataPtr, sizeTensorDataPtr+sizeTensorNumValues);
+
+ desc.m_TargetHeight = static_cast<uint32_t> (sizeTensorData[0]);
+ desc.m_TargetWidth = static_cast<uint32_t> (sizeTensorData[1]);
+ desc.m_DataLayout = armnn::DataLayout::NHWC;
+
+ // No network pointer indicates that only support for this operator should be checked
+ if (!delegateData.m_Network)
+ {
+ return ValidateResizeOperator(delegateData,
+ tfLiteContext,
+ inputTensorInfo,
+ outputTensorInfo,
+ desc);
+ }
+
+
+ armnn::IConnectableLayer* resizeLayer = nullptr;
+ resizeLayer = delegateData.m_Network->AddResizeLayer(desc, layerName.c_str());
+
+ armnn::IOutputSlot& outputSlot = resizeLayer->GetOutputSlot(0);
+ outputSlot.SetTensorInfo(outputTensorInfo);
+
+ // try to connect the Constant Inputs if there are any
+ if(ProcessInputs(resizeLayer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk )
+ {
+ return kTfLiteError;
+ }
+
+ ARMNN_ASSERT(resizeLayer != nullptr);
+
+ return Connect(resizeLayer, tfLiteContext, tfLiteNode, delegateData);
+}
+
+} // namespace armnnOpaqueDelegate